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Quantification of Margins and Uncertainties Approach for Structure Analysis Based on Evidence Theory

机译:基于证据理论的结构分析的余量和不确定性量化方法

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摘要

Quantification of Margins and Uncertainties (QMU) is a decision-support methodology for complex technical decisions centering on performance thresholds and associated margins for engineering systems. Uncertainty propagation is a key element in QMU process for structure reliability analysis at the presence of both aleatory uncertainty and epistemic uncertainty. In order to reduce the computational cost of Monte Carlo method, a mixed uncertainty propagation approach is proposed by integrated Kriging surrogate model under the framework of evidence theory for QMU analysis in this paper. The approach is demonstrated by a numerical example to show the effectiveness of the mixed uncertainty propagation method.
机译:保证金和不确定性量化(QMU)是一种复杂的技术决策的决策支持方法,其重点是工程系统的性能阈值和相关的保证金。在存在不确定性不确定性和认知不确定性的情况下,不确定性传播是QMU过程中结构可靠性分析的关键因素。为了降低蒙特卡洛方法的计算成本,本文在证据理论的框架下,提出了一种综合Kriging替代模型的混合不确定度传播方法,用于QMU分析。数值例子证明了该方法的有效性,表明了混合不确定度传播方法的有效性。

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  • 来源
    《Mathematical Problems in Engineering》 |2016年第6期|6419058.1-6419058.5|共5页
  • 作者

    Xie Chaoyang; Li Guijie;

  • 作者单位

    Univ Elect Sci & Technol China, Sch Mechatron Engn, Chengdu 611731, Peoples R China|China Acad Engn Phys, Inst Syst Engn, Mianyang 621900, Peoples R China;

    China Acad Engn Phys, Inst Syst Engn, Mianyang 621900, Peoples R China;

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